Research Intern - Hematopathology - Research
- Requisition #: 600652-202609231254
- Department: Hematopathology - Rsch
- Location: Houston, TX
- Posted Date: 9/21/2026
The Research Intern position is a short-term appointment that provides firsthand practical experience in the area of cancer research and insight into a variety of science career opportunities. The ideal trainee will join existing laboratory staff under the guidance of a designated faculty mentor to:
-Develop proficiency in slide scanning and digital pathology workflows.
-Understand AI models used for cell classification in leukemia diagnosis.
-Apply AI-based classification techniques to leukemia case studies.
This position offers hands-on exposure to emerging technologies in pathology and cancer research while supporting the development of technical and analytical skills in a collaborative research environment. NOTE: Research Interns are not allowed in clinics, patient care areas, or the OR.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
Objective 1: Develop Proficiency in Slide Scanning and Digital Pathology
Workflow:
o Introduction to Slide Scanners & Imaging Techniques, including hands-on training with whole-slide imaging (WSI) scanners.
o Understand scanner settings (resolution, focus, illumination), file formats (SVS, TIFF), and data storage.
o Acquire slides, organization, prepare and upload sample associated information using Epic.
o Practice scanning bone marrow and tissue slides, including aspirates, biopsies, peripheral blood smears, etc.; compare different scan settings and assess image quality.
o Quality Control and image preprocessing, detect common scanning artifacts (blurry regions, out-of-focus areas) and use preprocessing techniques (color normalization, contrast adjustment).
o Using software tools for basic annotations, evaluating image quality, and troubleshooting ability.
Objective 2: Understand AI Models for Cell Classification in Leukemia Diagnosis:
o Overview of AI-based cell classification models, basics of convolutional neural networks (CNNs) in image recognition, understanding dataset
requirements for training AI models.
o Hands-on Experience with Pre-Trained AI Models, running AI models on scanned images, AI-based classification of blasts, lymphocytes, and dysplastic cells.
o Comparing AI predictions with pathologist annotations.
o Evaluating Model Performance & Error Analysis, accuracy, sensitivity, and specificity; identifying common AI misclassifications.
o Run AI models on new datasets, present findings in a structured report.
Objective 3: Apply AI-Based Classification to Leukemia Case Studies:
o Reviewing Clinical Cases & Correlating with AI Predictions on leukemia cases (AML, ALL, MDS) with expert guidance, compare AI-based
classifications with pathology reports.
o Annotating & Labeling Training Data for AI Model Improvement, identification and labeling cells, participates in interobserver comparison with expert pathologists.
o Completes study project, writing abstract and manuscript, submits a final report with recommendations for model improvement.
ELIGIBILITY REQUIREMENTS
o Applicant must hold a bachelor's or master's degree; Degree must have been obtained recently (within one year)
o Applicant must have previous research experience;
o Applicants who hold a Ph.D. or equivalent doctoral degree (e.g., M.D., D.V.M., M.B.B.S.) are not eligible;
o Applicants associated with a home institution do not qualify;
o Applicants in a clinical position, postdoctoral fellowship, or faculty position do not qualify;
o Research Interns cannot change titles to another trainee title upon completion. Exception applies if the trainee enrolls in a degree-seeking program
o The appointee trains under the supervision of a faculty member/mentor
Term limit:
o Research Interns can be appointed part-time (0.5 FTE) or full-time (1.0 FTE);
o Research Interns must be appointed for a minimum of 30 days and a maximum of six months. Requests for extensions or reappointments beyond the six-month term will not be granted.
ADDITIONAL APPLICATION INFORMATION
The University of Texas M.D. Anderson Cancer Center is the #1 ranked cancer center in the US and has been committed to Making Cancer History® for more than 80 years. With integrated and comprehensive programs to advance impactful discovery, prevention, translational and clinical research, the institution engages some of the top minds in the world to gain a deeper understanding of cancer and to bring meaningful benefits to patients.
POSITION INFORMATION
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html
-Develop proficiency in slide scanning and digital pathology workflows.
-Understand AI models used for cell classification in leukemia diagnosis.
-Apply AI-based classification techniques to leukemia case studies.
This position offers hands-on exposure to emerging technologies in pathology and cancer research while supporting the development of technical and analytical skills in a collaborative research environment. NOTE: Research Interns are not allowed in clinics, patient care areas, or the OR.
All duties and responsibilities are carried out in compliance with institutional policies, ethical research standards, and applicable federal and state regulations.
LEARNING OBJECTIVES
Objective 1: Develop Proficiency in Slide Scanning and Digital Pathology
Workflow:
o Introduction to Slide Scanners & Imaging Techniques, including hands-on training with whole-slide imaging (WSI) scanners.
o Understand scanner settings (resolution, focus, illumination), file formats (SVS, TIFF), and data storage.
o Acquire slides, organization, prepare and upload sample associated information using Epic.
o Practice scanning bone marrow and tissue slides, including aspirates, biopsies, peripheral blood smears, etc.; compare different scan settings and assess image quality.
o Quality Control and image preprocessing, detect common scanning artifacts (blurry regions, out-of-focus areas) and use preprocessing techniques (color normalization, contrast adjustment).
o Using software tools for basic annotations, evaluating image quality, and troubleshooting ability.
Objective 2: Understand AI Models for Cell Classification in Leukemia Diagnosis:
o Overview of AI-based cell classification models, basics of convolutional neural networks (CNNs) in image recognition, understanding dataset
requirements for training AI models.
o Hands-on Experience with Pre-Trained AI Models, running AI models on scanned images, AI-based classification of blasts, lymphocytes, and dysplastic cells.
o Comparing AI predictions with pathologist annotations.
o Evaluating Model Performance & Error Analysis, accuracy, sensitivity, and specificity; identifying common AI misclassifications.
o Run AI models on new datasets, present findings in a structured report.
Objective 3: Apply AI-Based Classification to Leukemia Case Studies:
o Reviewing Clinical Cases & Correlating with AI Predictions on leukemia cases (AML, ALL, MDS) with expert guidance, compare AI-based
classifications with pathology reports.
o Annotating & Labeling Training Data for AI Model Improvement, identification and labeling cells, participates in interobserver comparison with expert pathologists.
o Completes study project, writing abstract and manuscript, submits a final report with recommendations for model improvement.
ELIGIBILITY REQUIREMENTS
o Applicant must hold a bachelor's or master's degree; Degree must have been obtained recently (within one year)
o Applicant must have previous research experience;
o Applicants who hold a Ph.D. or equivalent doctoral degree (e.g., M.D., D.V.M., M.B.B.S.) are not eligible;
o Applicants associated with a home institution do not qualify;
o Applicants in a clinical position, postdoctoral fellowship, or faculty position do not qualify;
o Research Interns cannot change titles to another trainee title upon completion. Exception applies if the trainee enrolls in a degree-seeking program
o The appointee trains under the supervision of a faculty member/mentor
Term limit:
o Research Interns can be appointed part-time (0.5 FTE) or full-time (1.0 FTE);
o Research Interns must be appointed for a minimum of 30 days and a maximum of six months. Requests for extensions or reappointments beyond the six-month term will not be granted.
ADDITIONAL APPLICATION INFORMATION
The University of Texas M.D. Anderson Cancer Center is the #1 ranked cancer center in the US and has been committed to Making Cancer History® for more than 80 years. With integrated and comprehensive programs to advance impactful discovery, prevention, translational and clinical research, the institution engages some of the top minds in the world to gain a deeper understanding of cancer and to bring meaningful benefits to patients.
POSITION INFORMATION
Offsite work arrangements are subject to approval and may be modified or revoked at any time based on business needs, performance considerations, or regulatory requirements.
This position may be responsible for maintaining the security and integrity of critical infrastructure, as defined in Section 113.001(2) of the Texas Business and Commerce Code and therefore may require routine reviews and screening. The ability to satisfy and maintain all requirements necessary to ensure the continued security and integrity of such infrastructure is a condition of hire and continued employment.
It is the policy of The University of Texas MD Anderson Cancer Center to provide equal employment opportunity without regard to race, color, religion, age, national origin, sex, gender, sexual orientation, gender identity/expression, disability, protected veteran status, genetic information, or any other basis protected by institutional policy or by federal, state or local laws unless such distinction is required by law. http://www.mdanderson.org/about-us/legal-and-policy/legal-statements/eeo-affirmative-action.html
